Correlated double sampling for noise reduction in magnetoresistive sensors and sensor arrays

ABSTRACT

Correlated double sampling (CDS) for magnetoresistive (MR) sensors is provided. Here the MR sensor output is sampled at two closely spaced times. The first sample is MR signal+baseline+noise and is sampled when the modulated magnetic field is non-zero. The second sample is baseline+noise only because it is sampled when the modulated magnetic field is zero. The difference between the first and second samples will have significantly reduced low frequency noise and baseline cancellation. Modulation of the electrical bias provided to the MR sensor can be used to provide a baseline signal for temperature compensation. In a second aspect, we provide MR sensor arrays having input and output multiplexing and demultiplexing for row and column line selection, in combination with a per-sensor switch to prevent noise accumulation and bandwidth reduction from idle MR sensors.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. provisional patentapplication 62/040,789, filed on Aug. 22, 2014, and hereby incorporatedby reference in its entirety.

FIELD OF THE INVENTION

This invention relates to magnetoresistive (MR) sensors.

BACKGROUND

Magnetoresistance is a change in electrical resistance that depends onmagnetic field. The presence of an object of interest (e.g., a magneticparticle) can be sensed by the change in resistance of the MR sensor.Biological assays can be constructed by making magnetic particles bindto MR sensors under biologically specific circumstances. For example, ifthe MR sensors and magnetic particles are coated with an antigen and acorresponding antibody, respectively or vice versa, then binding ofantibody to antigen can be detected via the MR effect.

In biological applications, it is often desired to employ a large arrayof MR sensors in order to conduct large-scale assays. In such cases,system performance is often limited by electrical noise, and noisemitigation is also of more general interest for all applications of MRsensors. Accordingly, it would be an advance in the art to mitigatenoise in MR sensors, especially in connection with arrays of MR sensors.

SUMMARY

The present work has two aspects, which can be practiced individually orin combination. The first aspect relates to use of correlated doublesampling (CDS) for MR sensors combined with modulation of an appliedmagnetic field. The second aspect relates to MR sensor arrays havinginput and output multiplexing and demultiplexing for row and column lineselection, in combination with a per-sensor switch to prevent noiseaccumulation from idle MR sensors.

This work provides correlated double sampling in connection with MRsensors. The MR sensor output is sampled at two closely spaced times.The first sample is MR signal+baseline+noise, and the second sample isbaseline+noise only. The difference between the first and second signalswill have baseline cancellation and significant noise suppressionbecause of the relatively low noise frequencies involved and becauseboth signals are provided by the same circuitry. Further elaborations ofthis approach (e.g., as described below) can be used to providelow-noise temperature correction for MR sensors, and suitablearchitectures for low-noise MR sensor arrays.

More specifically an MR sensor array can include an analog multiplexer(Mux) and demultiplexer (deMux) to provide column line and row lineselectors (or vice versa). Introduction of the Mux and the deMuxdramatically reduces the number of input/output pads of the microarraychip, which in turn greatly simplifies the interface with sensor readoutcircuits. Adopting a two dimensional matrix structure allows sensorelements to be individually accessible in time and also improves powerefficiency of the array.

Each magnetoresistive sensor in an array can have its own on/off switch.Using such switches, only sensors in selected pixels are accessible atthe readout time, while the other sensors are disconnected from the rowand/or column lines. This advantageously prevents noise from unselectedsensors from being transmitted to the input of readout circuits. Anotheradvantage of this methodology is to preserve the signal bandwidth of thereadout channel by disconnecting unread sensors from the channel.Without it, the signal bandwidth is narrowed due to the unread sensorsconnected to the channel. The switches can be metal-oxide-semiconductordevices or other semiconductor devices such as switching diodes. Thenumber of switching devices per sensor element can be one or more.

This can provide a broader scalability of magnetoresistive sensor arrayswhich can accommodate more than 1,000 sensors per array. In medicalapplications, demand for large-scale sensor arrays accommodatingnumerous types of analytes such as human proteins is increasing. Thiswork provides architectures for large-scale magnetoresistive sensorsarray without disadvantages in channel bandwidth and noise performance.Correlated double sampling and temperature correction techniques can beused to build temperature insensitive and high throughput dataacquisition systems using magnetoresistive sensors, although thetechniques are suitable for arrays with less than 1000 sensors as well.

These approaches are broadly applicable, e.g., in both biological andnon-biological settings. Applications include medical, mobile andindustrial applications of magnetoresistive sensors. Exemplary medicalapplications include diagnosis and/or prognosis of a disease and drugdiscovery targeting a specific disease. For mobile and industrialapplications, quantification of a minute change of the magnetic fieldand/or magnetically actuated reaction can be provided.

Significant advantages are provided.

1. Correlated double sampling and temperature correction methods canprovide ultra-high throughput in data acquisition in a large-scalesensor array with large dynamic range and high precision. For example,the readout speed per channel can be 100× faster with the CDS approachthan with prior approaches (e.g., lock-in double modulation techniquesas described below).

2. The MR sensor array architectures can provide constant channelbandwidth and fixed noise performance regardless of the number ofsensors in the array.

Several variations are possible. The biasing of the magnetoresistivesensors can be provided by a bias voltage or by a bias current. Amodulated magnetic field of square, sinusoidal or return-to-zerowaveform are suitable for CDS techniques. More generally, any modulationwaveform which includes a zero magnetic field portion of the waveformcan also be utilized.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a block diagram of an embodiment of the invention.

FIGS. 1B-D are exemplary images of magnetoresistive sensors.

FIG. 2A shows an exemplary binding curve for biomarker detection.

FIG. 2B shows exemplary transient binding curves for biomarkerdetection.

FIGS. 3A-B show exemplary noise spectra for MR sensors and electronics.

FIGS. 4A-B show the operation principle of correlated double samplingfor magnetoresistive sensors.

FIG. 5 shows an overall functional diagram for the data acquisitionsystem with correlated double sampling and temperature compensationtechniques.

FIG. 6A shows CDS for acquisition of the baseline signal.

FIG. 6B shows CDS for acquisition of the MR signal.

FIGS. 7A-D show experimental results of correlated double sampling forMR sensors.

FIGS. 8A-D show experimental results of correlated double samplingcombined with temperature compensation for MR sensors.

FIG. 9A-E show results from a binding experiment using magneticnanoparticles.

FIG. 10 shows a low noise architecture for an MR sensor array.

FIG. 11 shows a sensor readout example based on the architecture of FIG.10.

FIGS. 12A-D show AC and noise simulation results relating to thearchitecture of FIG. 10 (FIG. 12B and FIG. 12D) compared to aconventional MR sensor array (FIG. 12A and FIG. 12C).

DETAILED DESCRIPTION

A) Introduction

Molecular diagnostics is used extensively today by the medical communityfor disease diagnosis, prognosis, therapy monitoring and drug discovery.As researchers begin to understand the numerous biomarkers associatedwith complex diseases such as cancers, new sensing technologies emergeto effectively detect and measure the biomarkers of interest inpatients' samples. The demand for high sensitivity, broad linear dynamicrange, and large multiplexing capability requires high performancesensing technologies. Conventional optical techniques, which rely on afluorescent tag to label biomarkers of interest, have a limited dynamicrange due to the optical background noise and also inherently haverelatively low sensitivity. By replacing the fluorescent tag with amagnetic nanoparticle and the bulky optics with a magnetoresistive (MR)sensor, researchers have achieved highly sensitive detection with abroad linear dynamic range.

FIG. 1A schematically shows a magnetic particle 106 in proximity to a MRsensor 102. The presence of the magnetic field from magnetic particle106 at MR sensor 102 changes the electrical resistance of MR sensor 102.FIGS. 1B-D show images of exemplary MR sensors. FIG. 1B is an image of a64 element giant magnetoresistive (GMR) spin valve sensor array. FIG. 1Cis a magnified view of a single sensor in the array of FIG. 1B. MultipleGMR sensor strips form the GMR sensor. FIG. 1D is an image showing superparamagnetic nanoparticles on the surface of the GMR sensor.

The MR biosensor typically includes elaborately engineered thin filmstacks of magnetic and non-magnetic materials. Multiple narrow and longstrips of the thin film stacks form a MR sensor (FIGS. 1B-C). It sensesthe minute change of the induced magnetic field by the number ofmagnetic nanoparticles adjacent to it in the circumstance of theexternal magnetic field (FIG. 1D). The number of magnetic nanoparticlesis proportional to the degree of the reaction between the antibodies onthe sensor surface and the analytes. If the antibodies are paired withthe target analytes, the resistance of the MR sensor changes.

FIGS. 2A-B show examples of specific biomarker detection bymagneto-resistive sensors. FIG. 2A is a standard binding curve (Signalvs. concentration of CEA (Carcinoembryonic antigen, which is a cancerbiomarker)). FIG. 2B shows transient binding curves (Signal vs. time) ofthree biomarkers. BSA and epoxy is a biological control and a reference,respectively. A minute signal of interest is distinguishable from thecontrol.

Since the MR sensor has both magnetic and resistive characteristics, itgenerates noises such as 1/f noise, thermal noise, Barkhausen noise andso on. Barkhausen noise can be eliminated by utilizing shape anisotropyof the film strips and/or applying strong magnetic field to the sensorat the preconditioning step. If Barkhausen noise is excluded, 1/f noisedominates the total noise from the sensor at the low frequency range andthermal noise at the frequency range over the corner frequency of 1/fnoise. FIG. 3A shows voltage noise measured from an exemplary MR sensorat fixed current. Input voltage noise of the sensor is 4.76nV_(rms)/√Hz, which is close to the theoretical thermal noise floor4k_(B)TR. The 1/f noise corner frequency is at 285 Hz.

The signal of interest is commonly located at low frequency range, so1/f noise degrades the limit of signal detection. Not only 1/f noisefrom the sensor, but 1/f noise caused by data acquiring electronics isalso problematic. FIG. 3B shows an example of the noise profile of acommercial operational amplifier (OPA656 from Texas Instruments, Inc.),which shows the dominant 1/f noise at lower frequency range. 1/f noiseis noise that has a power spectral density proportional to 1/f. Thecorner is where the 1/f noise intersects the thermal noise.

In order to avoid the degradation of signal-to-noise ratio by 1/f noiseof the data acquisition electronics, the frequency division multiplexing(FDM) has been used to measure the change of MR ratio of the sensors forthe biological reactions between analytes and antibodies. However, asthe size of the sensor array increases, the non-ideal phenomena in FDMsuch as harmonic distortion become more prominent. Furthermore, the dataacquisition time for an entire sensor array will dramatically increaseso that using FDM in a large-scale sensor array is unappealing.

B) General Principles

FIG. 1A shows an exemplary embodiment of the invention. This embodimentis apparatus for magnetic field sensing where the apparatus includes:

1) a magnetic field source 104 configured to provide a modulatedmagnetic field, where the modulated magnetic field has intervals of zeromagnetic field intensity and/or zero crossings of magnetic fieldintensity;

2) one or more magnetoresistive sensors 102 having electricalresistances that depend on magnetic field intensity at locations of themagnetoresistive sensors, where the magnetoresistive sensors aredisposed in the modulated magnetic field; and

3) electrical circuitry 110 configured to provide electrical signalsthat depend on electrical resistances of the magnetoresistive sensors.

The electrical circuitry is further configured to sample the electricalsignals synchronously with the modulated magnetic field. Morespecifically, the electrical signals are sampled during the intervals ofzero magnetic field intensity of the modulated magnetic field and/or atthe zero crossings of magnetic field intensity of the modulated magneticfield to provide reference sampled data. The electrical signals aresampled at times the magnetic field intensity of the modulated magneticfield is non-zero to provide measurement sampled data. The apparatus isconfigured to provide a difference between the measurement sampled dataand the reference sampled data as a measurement output.

The net effect of this approach for handling the signals from the MRsensor is to cancel the baseline signal in the measurement output andalso to significantly reduce low frequency noise in the measurementoutput. Here the ‘baseline’ signal is the signal that is provided by amagnetoresistive sensor in the absence of a magnetic field. Note thatmagnetoresistance is a change in resistance caused by an appliedmagnetic field. For example, the resistance may change from R to R+ΔRdue to an applied magnetic field, and in this example R is the baselineand ΔR is the magnetoresistive effect. If a current I flows through thesensor, the baseline voltage signal is IR and the magnetoresistivevoltage signal is I ΔR. In practice, the total signal (e.g., I(R+ΔR)) ismeasured and then processed to determine the magnetoresistive part ofthe total signal. It is convenient to refer to these total signals frommagnetoresistive sensors as ‘measurement signals’ having corresponding‘measurement sampled data’, as above.

Practice of the invention does not depend critically on how thedifference between the measurement sampled data and the referencesampled data is provided. For example this difference can be provided byan analog difference circuit or by a digital difference circuit.Practice of the invention also does not depend critically on how themodulated magnetic field is provided to the MR sensors. However, it ispreferred for this field to be provided in a way that is suitable forintegration with MR sensor arrays. For example, the modulated magneticfield can be provided by field wires or integrated circuit tracesdisposed beneath the array of MR sensor elements.

The magnetic field modulation is preferably periodic. Suitable magneticfield modulation wave forms include, but are not limited to: sinusoids,square waves, and return to zero (RZ) waveforms. Any magnetic fieldmodulation wave form having zero crossings or intervals of zerointensity can be employed. Here a square wave (e.g., 1) of FIG. 4B) isdefined as periodic modulation between zero intensity and one othernon-zero magnetic field intensity, where the field intensity is heldconstant except when switching between the two states, and the switchingpattern is 0+0+0+0+ (or 0−0−0−0−) etc. A return-to-zero (RZ) modulation(e.g., 3) of FIG. 4B)is defined as periodic modulation between zerointensity and two other non-zero magnetic field intensities. Here thetwo non-zero magnetic field intensities have equal magnitude andopposite polarity. The field intensity is held constant except whenswitching between the three states, and the switching pattern is0+0−0+0− (or 0−0+0−0+) etc.

As described in greater detail below, the relation between sampling rateof the electrical signals and modulation frequency of the magnetic fielddepends on details of the CDS methods being employed. Common options arethe modulation frequency of the modulated magnetic field being 1/2 or1/4 of the sampling rate of the electrical signals.

In preferred embodiments, the apparatus further includes one or morebaseline suppressors configured to reduce the direct current (DC)baseline of the magnetoresistive sensors. This can be helpful forpreventing saturation when amplifying weak MR signals.

Temperature compensation is an important consideration when using MRsensors. One known approach to MR sensor temperature compensation relieson using the baseline signal to temperature correct the MR signal. SinceCDS removes the baseline signal from the measurement output, specialmeasures are needed to combine CDS and temperature compensation.

In an embodiment, the apparatus further includes bias circuitry 108 onFIG. 1A to apply an electrical bias to the magnetoresistive sensors 102,where the electrical bias is modulated synchronously with the modulatedmagnetic field between a first bias and a second bias.

The electrical signals are sampled during the intervals of zero magneticfield intensity of the modulated magnetic field and/or at the zerocrossings of magnetic field intensity of the modulated magnetic fieldand when the electrical bias is the first bias to provide first sampleddata.

The electrical signals are sampled during the intervals of zero magneticfield intensity of the modulated magnetic field and/or at the zerocrossings of magnetic field intensity of the modulated magnetic fieldand when the electrical bias is the second bias to provide secondsampled data.

The apparatus is further configured to provide a difference between thefirst sampled data and the second sampled data as a baseline output. Themeasurement sampled data is all sampled at times having the sameelectrical bias.

The apparatus is further configured to automatically determine atemperature-corrected measurement from the measurement output and thebaseline output, and to provide the temperature-corrected measurement asa temperature corrected output.

The first and second sampled data is sampled at two different electricalbias values and at zero magnetic field in order to provide a baselinesignal for temperature correction. Details of this are given in sectionD below.

The magnetoresistive sensors can be configured to be disposed in amagnetic field to be quantified that is superposed with the modulatedmagnetic field. For example, the magnetic field to be quantified can begenerated by magnetic particles 106 on FIG. 1A captured on or nearsurfaces of the magnetoresistive sensors. Suitable magnetic particlesinclude but are not limited to: superparamagnetic particles,antiferromagnetic particles, and ferromagnetic particles with near-zeroremanence. The magnetic particles can be conjugated to analytes ofinterest, and the apparatus can be configured to quantify the analytes(e.g., in a biological assay).

The second aspect of this work relates to low noise MR sensor arrayarchitectures. An exemplary embodiment is apparatus for magnetic fieldsensing, where the apparatus includes:

1) a 2-D array of magnetoresistive sensors (1002 on FIG. 10);

2) an analog demultiplexer (1004 on FIG. 10) for selectively providingexcitation to one of the rows or columns of the 2-D array; and

3) an analog multiplexer (1006 on FIG. 10) for selectively readingsignals out from one of the rows or columns of the 2-D array.

The demultiplexer and multiplexer function as row and column selectorsrespectively, or vice versa. Each magnetoresistive sensor (MR on FIG.10) of the 2-D array has an associated sensor switch (S on FIG. 10). Thesensor switches are configured to disable all sensors being read out bythe multiplexer except the sensor being driven by the demultiplexer(e.g., FIG. 11).

C) Correlated Double Sampling (CDS)

FIGS. 4A-B show operation principle of correlated double sampling formagnetoresistive sensors. FIG. 4A is a conceptual diagram. On/Off timingfor electrical switches are shown on the right box as {circle around(1)} and {circle around (2)}. They are non-overlapping. Note thatswitches inside the dotted box are physical switches in the electricalcircuitry, while the switches to the right of the magnetic excitationblock are not physical elements. Instead, they schematically representthe modulation of the magnetic field. FIG. 4B shows examples of suitablemagnetic field modulation wave forms: 1) square, 2) sinusoidal and 3)return-to-zero (RZ). {circle around (1)} when H field=0 and {circlearound (2)} when H field in non-zero.

In general terms, CDS is a known circuit design technique in order toeliminate background noise such as non-ideal offsets and 1/f noise frommeasured signals of interest. The basic idea is to first sample andstore background noise only in the form of electronic charges bycapacitors. Then signal+background is sampled and stored again rightafter the former capturing event. A difference circuit subtracts onefrom the other, and thereby only the signal of interest remains. Theorder of sampling events can be swapped. There are many examples ofutilization of the CDS technique. A common application is the integratedimage sensors widely used in cameras. Another research group hasproposed the CDS technique in connection with a capacitive positionsensing system.

In this work we provide a novel CDS technique to effectively suppressthe background noise and offsets of the magnetoresistive sensors (FIG.4A). It utilizes a modulated magnetic field as a signal excitationsource. A modulated magnetic field of square, sinusoidal orreturn-to-zero waveforms are applicable to our CDS techniques (FIG. 4B).Other types of waveform which passes zero magnetic field point can alsobe utilized. A conventional MR sensor and the sandwich assay techniquecan be utilized as a sensor and its biological interface. Since MRsensors respond to the in-plane magnetic fields on their magnetic freelayers, the presence of the modulated field changes themagnetoresistance of the sensors. If there is zero magnetic field, asensor under test produces only baseline signal and noise. On the otherhand, it will produce finite magnetoresistive signal as well as baselinesignal and noises in the presence of non-zero magnetic field. Providedthat temporal difference between two measurements ({circle around (1)}and {circle around (2)}) is sufficiently small, the 1/f noise and offsetfrom sensors and electronics at {circle around (1)} and {circle around(2)} become highly correlated and thereby the subtraction between twomeasured data will remove a large portion of 1/f noise and offset.Therefore a signal having reduced 1/f noise and reduced offset can beobtained using the present CDS technique.

D) Correlated Double Sampling with Temperature Correction

Because the MR sensor has both resistive and magnetoresistiveproperties, it has not only the temperature coefficient of resistance(TCR) but also the temperature coefficient of magnetoresistance (TCMR).Because the MR signal obtained by the present CDS technique is a complexfunction of TCR and TCMR and it is sensitive to the temperature change,a special temperature correction treatment is required. In this work, weshow how to provide temperature correction for the CDS MR sensortechnique.

FIG. 5 shows the overall functional diagram for the data acquisitionsystem with CDS and TC techniques. This signal path is utilized for themeasurement of both the CDS signal and the baseline signal.

In order to minimize the temperature fluctuation effect on the sensor inCDS, the system with a proper temperature correction (TC) technique isprovided (e.g., FIG. 5). In order to increase the gain of the signalpath without saturation, the baseline suppressor is introduced. Thesuppressor can be any circuit having the effect of reducing the baselinefrom the MR sensors. For example, the suppressor can be a currentsource, current-mode digital to analog converter, or a R-2R ladder toincrease the tolerance against the process variation of the MR sensor.The output of the baseline suppressor subtracted from the output of MRsensor under no magnetic field is the net baseline signal comparable tothe magnitude of the MR signal. The suppressed baseline and MR signalare amplified and provided to the correlated double sampler. Theprocessed signal can be digitized and filtered in the digital domain.Finally, a novel temperature correction algorithm eliminates temperaturedrift noise from the measured data which can be realized in the softwaredomain.

The baseline signal is used to extract the degree of the temperaturedrift at the moment, and the extracted information of temperature driftis utilized to compensate the measured MR signal to make it temperatureinsensitive. Because the CDS operation for obtaining MR signal (V_(MR))also removes the baseline signal from measured signal, a unique methodto measure only the baseline signal (V_(BASE)) is necessary. In order toimprove the performance of the temperature correction, V_(BASE) shouldbe 1/f noise and offset-reduced. It employs an additional CDS phaseduring the operation.

FIG. 6A shows correlated double sampling technique for 1/f noise andoffset-reduced baseline signal. FIG. 6B shows correlated double samplingtechnique for 1/f noise and offset-reduced MR signal detection. In FIG.6A, the electrical bias voltage into the MR sensor is given pulsed form.In FIG. 6B, the pulsed external magnetic field (schematically shown bytwo coil symbols around R) is provided to the sensor, thereby changingthe resistance of the MR sensor. R and Rc are the MR sensor and thebaseline suppressing resistor, respectively. Dots on the timing graphindicate the moments to be sampled at the correlated double sampler.

Here we provide the novel correlated double sampling techniques tomeasure both the 1/f noise and offset-reduced baseline signal and the MRsignal (FIGS. 6A-B). The virtues of this approach include: 1) thesimplicity in the circuit design because the correlated double samplingin FIGS. 6A-B shares most of the signal path; and 2) the magnetic fieldmodulation is utilized in the correlated double sampling. To measure the1/f noise and offset-reduced baseline signal, the bias voltage excitingthe MR sensor R gets a pulsed form. It changes from V to V+ΔV and goingback to V (FIG. 6A). CDS operation is done by sampling the baselinesignal with respect to these two levels. The path output V_(BASE) is

$V_{BASE} = {{( {( {\frac{V + {\Delta\; V}}{R} + \frac{- V}{R_{C}}} ) - ( {\frac{V}{R} + \frac{- V}{R_{C}}} )} )G_{PATH}} = {\frac{\Delta\; V}{R}G_{PATH}}}$$R = {\frac{\Delta\; V}{V_{BASE}}G_{PATH}}$where G_(PATH) is the transimpedance gain of the analog circuits. SinceV_(BASE) results from the CDS operation, it is 1/f noise andoffset-reduced. So is R.

For measuring the MR signal, the pulsed external magnetic field from 0to ΔH is applied to the MR sensor (FIG. 6B). Its resistancecorresponding to the field changes from R to R+ΔR. The MR signal involtage, V_(MR), is

$V_{MR} = {{( {( {\frac{V}{R + {\Delta\; R}} + \frac{- V}{R_{C}}} ) - ( {\frac{V}{R} + \frac{- V}{R_{C}}} )} )G_{PATH}} \approx {{- \frac{\Delta\; R}{R^{2}}}G_{PATH}V}}$$\frac{\Delta\; R}{R^{2}} \approx {- \frac{V_{MR}}{G_{PATH}V}}$Like the former case,

$\frac{\Delta\; R}{R^{2}}$is 1/f noise and offset-reduced.

Because the sensors are resistive, the expression of the measured outputvoltage depends on the type of excitation methods: voltage and currentexcitation. A common voltage excitation method generates the outputvoltage containing the reciprocal terms of the resistance of sensors. Onthe other hand, a common current excitation method produces the outputvoltage including the proportional terms of the resistance of sensors.An example derivation for the output signal of the current excitationmethod is shown here.V _(out) =I·R=IR ₀(1+αT)where I and α is the excitation current and the temperature coefficientof resistance, respectively.

We provide here a new temperature correction algorithm suitable for usein connection with CDS MR sensors.

We define the following terms.

-   G_(PATH): temperature insensitive transimpedance gain of the analog    circuits-   R₀, ΔR₀: temperature independent resistance and magnetoresistance,    respectively-   α, β: temperature coefficient of nominal resistance and    magnetoresistance, respectively-   V_(MR,measured)(t): the measured MR signal (temperature sensitive)-   V_(BASE,measured)(t): the measured baseline signal (temperature    sensitive)-   V_(MR,corrected)(t): the desired MR signal after temperature    correction-   ΔT: temperature change at time t comparing to the initial    temperature at time 0-   In the ideal condition where temperature does not change, V_(MR) and    V_(BASE) are as follows:

${V_{{MR},{Ideal}}(t)} = {{G_{PATH}{V( {\frac{1}{R_{0} + {\Delta\; R_{0}}} - \frac{1}{R_{0}}} )}} \approx {- \frac{G_{PATH}V\;\Delta\; R_{0}}{R_{0}^{2}}}}$${V_{{BASE},{ideal}}(t)} = \frac{G_{PATH}\Delta\; V}{R_{0}}$Including temperature fluctuation effect, V_(MR) and V_(BASE) become

${V_{{MR},{measured}}(t)} = {{- \frac{G_{PATH}V\;\Delta\; R_{0}}{R_{0}^{2}}} \cdot \frac{1 + {{\beta\Delta}\; T}}{( {1 + {{\alpha\Delta}\; T}} )^{2}}}$${V_{{BASE},{measured}}(t)} = \frac{G_{PATH}\Delta\; V}{R_{0}( {1 + {{\alpha\Delta}\; T}} )}$Initial values of these two terms at time 0 are as follows.

${V_{{MR},{measured}}(0)} = {- \frac{G_{PATH}V\;\Delta\; R_{0}}{R_{0}^{2}}}$${V_{{BASE},{measured}}(0)} = \frac{G_{PATH}\Delta\; V}{R_{0}}$Normalizing the MR signal and the baseline signal to their initialmagnitude at time 0,

$\frac{V_{{MR},{measured}}(t)}{V_{{MR},{measured}}(0)} = \frac{1 + {{\beta\Delta}\; T}}{( {1 + {{\alpha\Delta}\; T}} )^{2}}$$\frac{V_{{BASE},{measured}}(t)}{V_{{Base},{measured}}(0)} = \frac{1}{1 + {{\alpha\Delta}\; T}}$First, the temperature dependent component of the nominal resistance ina MR sensor is derived.

${{\alpha\Delta}\; T} = {\frac{V_{{BASE},{measured}}(0)}{V_{{Base},{measured}}(t)} - 1}$Next, the temperature dependent component of the magnetoresistance isexpressed as follows.

${{\beta\Delta}\; T} = {{{\frac{V_{{MR},{measured}}(t)}{V_{{MR},{measured}}(0)} \cdot ( {1 + {{\alpha\Delta}\; T}} )^{2}} - 1} = {{\frac{V_{{MR},{measured}}(t)}{V_{{MR},{measured}}(0)} \cdot ( \frac{V_{{BASE},{measured}}(0)}{V_{{BASE},{measured}}(t)} )^{2}} - 1}}$The ratio of the temperature coefficient of MR to that of nominal R isdefined here.

$\kappa\overset{\Delta}{=}{\frac{\beta}{\alpha} = \frac{{\frac{V_{{MR},{measured}}(t)}{V_{{MR},{measured}}(0)} \cdot ( \frac{V_{{BASE},{measured}}(0)}{V_{{BASE},{measured}}(t)} )^{2}} - 1}{\frac{V_{{BASE},{measured}}(0)}{V_{{BASE},{measured}}(t)} - 1}}$The equation of V_(MR,measured) can be represented without twotemperature coefficients.

${V_{{MR},{measured}}(t)} = {{- \frac{G_{PATH}V\;\Delta\; R_{0}}{R_{0}^{2}}} \cdot \frac{1 + {\kappa( {\frac{V_{{BASE},{measured}}(0)}{V_{{BASE},{measured}}(t)} - 1} )}}{( \frac{V_{{BASE},{measured}}(0)}{V_{{BASE},{measured}}(t)} )^{2}}}$In order to desensitize it from temperature fluctuation, we can multiplyit with the term below.

${V_{{MR},{corrected}}(t)} = {{{V_{{MR},{measured}}(t)} \cdot \frac{( \frac{V_{{BASE},{measured}}(0)}{V_{{BASE},{measured}}(t)} )^{2}}{1 + {\kappa( {\frac{V_{{BASE},{measured}}(0)}{V_{{BASE},{measured}}(t)} - 1} )}}} = {- \frac{G_{PATH}V\;\Delta\; R_{0}}{R_{0}^{2}}}}$So the temperature insensitive magnetoresistive voltage output isderived only with the V_(MR,measured) and V_(BASE,measured), without theknowledge of the temperature coefficients of both nominal resistance andmagnetoresistance of the MR sensor.

The algorithm for the temperature correction in case of currentexcitation on MR sensors is also given here.V _(MR,ideal)(t)=A _(PATH) I((R ₀ +ΔR ₀)−R ₀)=A _(PATH) IΔR ₀Considering temperature fluctuation,

${V_{{MR},{measured}}(t)} = {{A_{PATH}I\;\Delta\;{R_{0}( {1 + {{\beta\Delta}\; T}} )}} = {A_{PATH}I\;\Delta\;{R_{0}( {1 + {\kappa( {\frac{V_{{BASE},{measured}}(t)}{V_{{BASE},{measured}}(0)} - 1} )}} )}}}$  where$\mspace{20mu}{\kappa\overset{\Delta}{=}{\frac{\beta}{\alpha} = \frac{\frac{V_{{MR},{measured}}(t)}{V_{{MR},{measured}}(0)} - 1}{\frac{V_{{BASE},{measured}}(t)}{V_{{BASE},{measured}}(0)} - 1}}}$

-   A_(PATH): temperature insensitive voltage gain of the analog    circuits

Temperature desensitization is done by this multiplication.

${V_{{MR},{corrected}}(t)} = {{{V_{{MR},{measured}}(t)} \cdot \frac{1}{1 + {\kappa( {\frac{V_{{BASE},{measured}}(t)}{V_{{BASE},{measured}}(0)} - 1} )}}} = {A_{PATH}I\;\Delta\; R_{0}}}$E) Experimental Work

FIGS. 7A-D show experimental results of correlated double sampling. FIG.7A shows measured referred to input noise (RTI) in baseline. γ is theslope of the 1/f noise. Typically 0.5≤γ≤2. FIG. 7B shows the CDS effecton the results of FIG. 7A. The 1/f noise is eliminated. FIG. 7C showsmeasured referred to input noise (RTI) in the magnetoresistive signal.FIG. 7D shows the CDS effect on the results of FIG. 7C. Most of the 1/fnoise is suppressed.

FIGS. 8A-D show experimental results demonstrating temperaturecorrection technique. FIG. 8A shows the response of nominal resistanceto the temperature change due to the cold hexane solution applied at sixminutes. FIG. 8B shows the response of magnetic resistance. κ (the ratioof TCMR to TCR) is −5.11 and it will be used in the temperaturecorrection of ΔR. FIG. 8C shows the response of magnetic resistance. Rand ΔR are simultaneously measured using CDS. FIG. 8D shows the measuredAMR ratio (dash curve) and the corrected AMR ratio (solid curve) usingthe present temperature correction in ppm. The corrected AMR ratio staysat around the 0 ppm regardless of the temperature change.

FIG. 9A shows results from a binding experiment using magneticnanoparticles. This plot shows binding curves for five sensors, one ofwhich is covered by the thick passivation layer and serves as a control.The control cannot be influenced by nanoparticles on the thickpassivation layer because the distance between particles and the controlis beyond the limit of the proximity effect of the particles. The errorbar represents the noise from binding kinetics and measurement setup.

FIG. 9B is an SEM image of sensor 1. Particle coverage is 51.02%. FIG.9C is an SEM image of sensor 2. Particle coverage is 16.03%. FIG. 9D isan SEM image of sensor 3. Particle coverage is 12.85%. FIG. 9E is an SEMimage of sensor 4. Particle coverage is 7.67%.

Experiments to confirm the functionality of the present CDS and TCtechniques have been conducted using GMR SV sensors arrays (FIGS. 7A-Dand 8A-D). If CDS is not performed in the acquisition of VBASE,measuredand VMR,measured, these signals will be contaminated with explicit 1/fnoise (FIGS. 7A and 7C). The amplitude of the 1/f noise overwhelms theeffect of temperature change on the sensors, thereby temperaturecorrection will not properly work. Utilizing the present CDS techniquein the measurement can effectively suppress 1/f noise from the measuredsignals (FIGS. 7B and 7D). The evaluation result of the present TC isshown in FIGS. 8A-D. When the cold hexane solution is applied to thesensor surface at six minutes, the nominal resistance (R0) and MRrapidly changes corresponding to the abrupt temperature change (FIGS. 8Aand 8C). As time goes on, surface temperature starts to return to theoriginal temperature and R0 and MR are restored to the initial values.The ratio of two temperature coefficients is constant regardless of thetemperature change (FIG. 8B). With the information of temperature driftextracted from the R0 change, the measured MR can be madetemperature-insensitive using the present TC technique (FIG. 8D).

FIGS. 9A-E show results from a binding experiment with Fe₃O₄superparamagnetic nanoparticles of 15 nm in diameter using chemicalabsorption between Polyethylenimine and the surfactant of the particles.The reaction can be quantitatively measured. Validation of thequantitative result in FIG. 9A has been done analyzing SEM imagesthrough the percentage of the area coverage by nanoparticles (FIGS.9B-E). Therefore it is demonstrated through the experiments that thecombination of the present CDS and temperature correction techniques iseffective to produce a noise resilient output from magnetoresistivesensors.

To better appreciate this work, we briefly compare these results toearlier double modulation work. This earlier work utilizes doublemodulation and the Fast Fourier Transform (FFT) to separate theanalyte-related signals from background noise and harmonics. In spite ofits high frequency resolution and superior thermal noise profile byfrequency binning, FFT requires a large number of samples taken for 500milliseconds to provide a frequency resolution of 2 Hz. It has anadditional timing penalty to complete post-processing using measuredsamples, which is comparable to or more than sampling time, e.g., in theorder of seconds. These considerations lead to a conclusion that thespectral analysis is not favorable to the large-scale magnetoresistive(MR) sensor array system regardless of in-pixel switching. In order toenhance the readout performance, we need to explore a different readoutscheme other than spectral analysis.

Generally, a large-scale sensor array contains a thousand or moresensors. In order to guarantee real time analysis using amagnetoresistive biosensor array, the system needs to measure the entirearray within a specified period of time. Despite the conventionalspectral analysis having good SNR performance, a long readout time percolumn (or channel) can be a fatal disadvantage for real time analysisin bioassays. So fast readout performance is crucial to large-scale MRsensor arrays and corresponding measurement systems.

Correlated double sampling (CDS) as described above can help solve thisproblem. Basically this technique has been developed in order tomitigate 1/f noise, which is a significant source of noise harming thereadout performance of circuits. Theoretically CDS operation just needstwo subsequent data acquisitions. If the temporal difference between twoacquisitions Δt is getting smaller, CDS can produce 1/f noise-reducedoutput signals at high speed. This exactly meets our needs to build ahigh speed data acquisition circuits for large-scale MR sensor arrays.In order to lower the thermal noise, multiple samples of CDSmeasurements can be taken then averaged. The above described experimentsfor the proof-of-concept demonstrate that the readout throughput of 48.8samples per second per channel was achieved when the magnetic field wasmodulated at 3.125 kHz (2 CDS samples were taken during each period ofthe field modulation, so the CDS sampling rate was 6.25 KHz) and the 64CDS output samples are averaged in experiments. These results are 24.4times faster than the throughput of the conventional double modulationtechnique with assumptions that the FFT processing penalty is neglectedand frequency division multiplexing is not utilized. Therefore, thereadout time according to this work is shown to be faster than theconventional spectral analysis and is favorable to the large-scale MRsensor array and system.

F) Low Noise MR Sensor Array Architecture

Conventional MR sensors arrays consist of only MR sensors and wires in atwo dimensional matrix structure like Random Access Memories. They havebeen scaled up by simply increasing the number of rows and columns.Sensor arrays of this kind having up to 256 elements have beendemonstrated.

There is a need for a large-scale microarray to accommodate numerousanalyte types of interest among the more than hundreds of thousands ofanalytes such as human proteins in some biological applications. Theconventional way to increase only the number of sensors and wires tomore than 256 is hardly achievable because it scales poorly.Connectivity is poor (more pads are required), noise is worse andchannel bandwidth is undesirably narrowed.

We provide a MR sensor array architecture which can accommodate morethan 10,000 sensors per array. FIG. 10 shows an example. Here 1002 is anMR sensor array. The number of rows and columns can be larger than 100and thereby more than 10,000 MR sensors can be in the array. The numberof pins (or pads) is minimized by utilizing an analog multiplexer 1006and demultiplexer 1004. Each pixel (e.g., 1008) includes one switch Sand one magnetoresistive sensor MR. However, there can be variations forthe number of switches inside the pixel. An excitation source 1010 candrive either voltage or current to the sensor array, while multiplexer1006 provides signals to readout circuitry 1012.

One of the key features of this large-scale MR sensor array is that ithas a pair of analog multiplexer (Mux) and demultiplexer (deMux) ascolumn line (heavy dashed lines e.g., 1020) and row line (heavy solidlines e.g., 1018) selectors, respectively. In the example of FIG. 10,1014 is the row selection input to demultiplexer 1004, and 1016 is thecolumn selection input to multiplexer 1006. Introduction of the Mux andthe deMux dramatically reduces the number of input/output pads of themicroarray chip, which in turn greatly simplifies the interface withsensor readout circuits. Adopting a two dimensional matrix structuremakes the large-scale sensor array to be randomly accessible in time andto be power efficient. However, the fabrication of this array can becomplex since both CMOS processes for analog Mux/deMux and non-CMOS postfabrication processes for MR sensors are required, which may increasethe total fabrication cost. This cost issue can be resolved by adoptingadvanced semiconductor fabrication techniques for mass production.

The other key feature is to introduce a switch S (e.g., ametal-oxide-semiconductor (MOS) device) for each pixel as an on/offswitch of a sensor. Only sensors in selected pixels are accessible atspecific readout time via a turn-on MOS switch and others aredisconnected to the column lines to be read by data acquisitioncircuits. FIG. 11 shows a sensor readout example. Here the pixel at row1 and column 1 is measured through a turned-on switch, and the state ofall switches is shown by ‘ON’ or ‘OFF’ on the figure. Noise generatedfrom other sensors on column 1 is rejected by the turned-off switches.Thus other sensors become transparent when a sensor at row 1 and column1 is read out by the following readout circuitry on column 1, whichimproves signal to noise ratio of the data acquisition system.Furthermore, disconnecting unused MR sensors from the column lines alsoprevents the signal bandwidth of a readout channel from being narrowed.

These benefits are demonstrated by an analog circuit simulation as shownon FIGS. 12A-D. These results are from AC simulation and noisesimulation results of a transimpedance amplifier which reads an MRsensor out of at most 128 sensors per column. FIGS. 12A and 12C showmagnitude and cumulative output noise, respectively, for a conventionalMR sensor array (no per-pixel switches). Note that N indicatesadditional MR sensors attached to the same channel. As N increases, thechannel bandwidth gets narrower and the output noise profile gets worse.Both bandwidth and output noise of the amplifier are heavily dependenton the number of sensors per column.

FIGS. 12B and 12D show magnitude and cumulative output noise,respectively, for a sensor array as on FIG. 10 (i.e., includingper-pixel switches). Neither bandwidth nor output noise changes as thenumber of sensors per column increases.

MOS switches for the large-scale MR sensor array are preferred becauseof their good on/off switching performance. However MOS switches are notrequired for practicing the invention. For example, switching diodes canalso be utilized in a large-scale MR sensor array as signal switches fora simpler implementation.

The invention claimed is:
 1. Apparatus for magnetic field sensing, theapparatus comprising: a magnetic field source configured to provide amodulated magnetic field, wherein the modulated magnetic field hasintervals of zero magnetic field intensity and/or zero crossings ofmagnetic field intensity; one or more magnetoresistive sensors havingelectrical resistances that depend on magnetic field intensity atlocations of the magnetoresistive sensors, wherein the magnetoresistivesensors are disposed in the modulated magnetic field; electricalcircuitry configured to provide electrical signals that depend onelectrical resistances of the magnetoresistive sensors; wherein theelectrical circuitry is further configured to sample the electricalsignals synchronously with the modulated magnetic field; wherein theelectrical signals are sampled during the intervals of zero magneticfield intensity of the modulated magnetic field and/or at the zerocrossings of magnetic field intensity of the modulated magnetic field toprovide reference sampled data; wherein the electrical signals aresampled at times the magnetic field intensity of the modulated magneticfield is non-zero to provide measurement sampled data; wherein theapparatus is configured to provide a difference between the measurementsampled data and the reference sampled data as a correlated doublesampling measurement output.
 2. The apparatus of claim 1, wherein thedifference between the measurement sampled data and the referencesampled data is provided by an analog difference circuit.
 3. Theapparatus of claim 1, wherein the difference between the measurementsampled data and the reference sampled data is provided by an digitaldifference circuit.
 4. The apparatus of claim 1, wherein the magneticfield modulation is periodic.
 5. The apparatus of claim 4, wherein themagnetic field modulation wave form is selected from the groupconsisting of: sinusoids, square waves, and return to zero (RZ)waveforms.
 6. The apparatus of claim 1, further comprising one or morebaseline suppressors configured to reduce a direct current (DC) baselineof the magnetoresistive sensors.
 7. The apparatus of claim 1, furthercomprising bias circuitry to apply an electrical bias to themagnetoresistive sensors, wherein the electrical bias is modulatedsynchronously with the modulated magnetic field between a first bias anda second bias; wherein the electrical signals are sampled during theintervals of zero magnetic field intensity of the modulated magneticfield and/or at the zero crossings of magnetic field intensity of themodulated magnetic field and when the electrical bias is the first biasto provide first sampled data; wherein the electrical signals aresampled during the intervals of zero magnetic field intensity of themodulated magnetic field and/or at the zero crossings of magnetic fieldintensity of the modulated magnetic field and when the electrical biasis the second bias to provide second sampled data; wherein the apparatusis further configured to provide a difference between the first sampleddata and the second sampled data as a baseline output; wherein themeasurement sampled data is all sampled at times having the sameelectrical bias; wherein the apparatus is further configured toautomatically determine a temperature-corrected measurement from themeasurement output and the baseline output, and to provide thetemperature-corrected measurement as a temperature corrected output. 8.The apparatus of claim 1, wherein the electrical signals have a samplingrate, and wherein a modulation frequency of the modulated magnetic fieldis 1/2 or 1/4 of the sampling rate of the electrical signals.
 9. Theapparatus of claim 1, wherein the magnetoresistive sensors areconfigured as a 2-D array, and further comprising: an analogdemultiplexer for selectively providing excitation to one of the rows orcolumns of the 2-D array; an analog multiplexer for selectively readingsignals out from one of the rows or columns of the 2-D array; whereinthe demultiplexer and multiplexer function as row and column selectorsrespectively, or vice versa; wherein each magnetoresistive sensor of the2-D array has an associated sensor switch, and wherein the sensorswitches are configured to disable all sensors being read out by themultiplexer except the sensor being driven by the demultiplexer.
 10. Theapparatus of claim 1, wherein the magnetoresistive sensors areconfigured to be disposed in a magnetic field to be quantified that issuperposed with the modulated magnetic field.
 11. The apparatus of claim10, wherein the magnetic field to be quantified is generated by magneticparticles captured on or near surfaces of the magnetoresistive sensors.12. The apparatus of claim 11, wherein the magnetic particles areselected from the group consisting of: superparamagnetic particles,antiferromagnetic particles, and ferromagnetic particles with near-zeroremanence.
 13. The apparatus of claim 11, wherein the magnetic particlesare conjugated to analytes of interest, and wherein the apparatus isconfigured to quantify the analytes.